Sweetness Adaptation of Some Carbohydrate and High Potency Sweeteners

A sip-and-swallow procedure designed to provide stimulation resembling normal drinking was employed to investigate adaptation to sweetness and sourness over time in a model beverage system. Intensity judgements were made using magnitude estimation. Adaptation to sweeteners (sucrose, HFCS, sucralose and aspartame) alone and in blends was evaluated. Different degrees of sweetness adaptation were observed. Sucrose and HFCS displayed less adaptation than the high potency sweeteners, sucralose and aspartame. Blends containing two high potency sweeteners adapted to a greater degree than the individual components. Blends containing a carbohydrate and a high potency sweetener showed less adaptation than those containing two high intensity sweeteners. Sourness adaptation was not demonstrated.     

Relationships of Sweetness in Lager to Selected Volatile Congeners

Lager is generally brewed to minimise the final sugar content but despite this can have sweet characters. Such flavour notes have been ascribed to concentrations above flavour thresholds of certain volatile congeners: maltol; 4‐hydroxy‐2,5‐dimethyl‐3(2H)‐furanone (HDMF); 4‐hydroxy‐2(5)‐ethyl‐5(2)‐methyl‐3(2H)‐furanone (HEMF); hydroxymethylfurfural (HMF); diacetyl; and specific esters (ethyl acetate, ethyl caproate, ethyl caprylate, and iso amyl acetate). Relationships between scoring of sweetness in lagers and quantitative data on relevant congeners and ethanol were explored. Lagers (23) were scored for sweetness using rank rating and in 18 lagers ten relevant volatile congeners were quantified by gas chromatography. Relationships between sensory and compositional data were modelled. Multiple linear regression was less successful than partial least squares regression (PLS1) based on four principal factors. Calibration values for r²were 0.70 and 0.77, when ester data was excluded and included, and validation values were 0.56 and 0.45, respectively. Prediction was improved to a validation r²= 0.74 when an artificial neural network was used in modelling with the complete compositional data set. It was concluded that in lagers a range of congeners and ethanol contribute in a complex manner to perceptions of sweetness and the relationship with 4‐hydroxyfuranone derivatives merits revaluation.     

Time Intensity Parameters of Sweetness Perceptions in Lager Beers

Lagers are generally brewed to minimise the final sugar content. Residual saccharides, derived from starch, contribute little to sweetness. Despite this, certain lagers exhibit sweet characters. These have not been explored in lagers, but are thought to originate from: maltol; 4‐hydroxy‐2,5‐dimethyl‐3(2H)‐furanone (HDMF); 4‐hydroxy‐2(or 5)‐ethyl‐5(or 2)‐methyl‐3(2H)‐furanone (HEMF); hydroxymethylfurfural (HMF); diacetyl; and certain esters (ethyl acetate, ethyl caproate, ethyl caprylate, and iso amyl acetate). This study used time‐intensity (TI) profiling, employing 13 assessors, to study sweetness in 10 lagers, scored similarly for sweetness in rank rating. Single intensity maxima were obtained with all products and all assessors. Data were analysed using ANOVA of curve parameters and non‐centred and centred principal component analyses (PCA). In ANOVA only the area under curve (A_tot) values differed significantly. However, shape of TI profile, or signature, differed between assessors who could on this basis be divided into two groups. In the multivariate data analyses, non‐centred PCA showed significant differences between lagers, parametric modelling and conventional PCA did not. However TI profile data suggested sweetness intensity perceived over the 120 seconds following ingestion could differ, although differences in scoring in rank rating were not significant.     

Assignation of Sweet Cherry Selections to 3 Taste Groupings Based on Perceived Sweetness and Sourness

ABSTRACT: Providing consumers with basic taste properties of sweet cherries at point of purchase would allow consumers to make purchase decisions based on fruit's intrinsic sensory attributes. The objective of this study was to develop a model to predict taste-grouping assignation of cherries into the following categories: (1) low sweetness/high sourness, (2) balance between sweetness and sourness, and (3) high sweetness/low sourness. A sensory panel (n = 10) was trained to recognize sweetness and sourness in 5 cultivars of sweet cherries and assign a taste grouping based on the perceived balance of sweetness and sourness. Four of these same cultivars were then evaluated for sweetness and sourness by a consumer panel (n = 117) and instrumentally for titratable acidity (TA) and soluble solids concentration (SSC). Results showed that for 3 of the 4 cherry cultivars, the sweetness/sourness balance of the cherries was not significantly different as evaluated instrumentally or by the trained panel. However, the balance determined by the consumer and the trained panel was different for 3 of the 4 cherry cultivars (P < 0.05). Based on trained panel perceived sweetness and sourness, a multinomial logit model was developed to predict the assignation of cherry taste grouping. The likelihood of group assignment depended on both the perceived sweetness and sourness of the cherry, with taste groupings agreed upon for 3 of 5 sweet cherry cultivars. As previous studies have indicated a positive relationship between cherry sweetness and sourness to consumer acceptance, these groupings show promise for assisting consumers in cherry selection at the point of purchase. Practical Applications: The prediction models proposed in this study suggest that both sweetness and sourness are important in the cherry characterization and the ratio between the 2 attributes may be appropriate for making taste-grouping assignments. These groupings may then be used to provide additional sensory information to consumers to assist them in cherry selection at the point of purchase.     

食用甜味剂的评价方法

本文对甜味剂评价过程中的评定人员．评价方法，以及对复合甜味剂的评价方法作了介绍，并介绍了利用电享舌和电子鼻评价、舌甘味剂的方法。     

Enhanced Sweetness in Sweetener-NaCI-Gum Systems

Enhancement of sweetness in aqueous gum (0.03%, w/v) sweetener systems by added NaCl (0.05%, w/v) was evaluated by a sensory panel. ²³Na NMR spectroscopy was used to determine Na⁺ binding and its relationship to sweetness elicited by glucose, lactose, maltose, sucrose and aspartame. Sweetness intensity differed due to gum (p = 0.0001) and sweetener (p = 0.0001), but was not affected by NaCl (p = 0.0774). Sweetness increased with added NaCl in xanthan, guar and locust bean gum solutions. However, sweetness decreased in k-carrageenan systems possibly due to endogenous cation (Ca²⁺, K⁺ and Na⁺) content, which influences Na⁺ mobility. The sweetest systems containing lactose and/ or xanthan, showed the greatest enhancement by NaCl.     

Non-destructive determination of acid–brix ratio of tomato juice using near infrared spectroscopy

Consumer's acceptance of tomato juice depends on its sourness to sweetness ratio and measuring this is important for quality control and marketing. Traditional methods destroy the samples, are time consuming and cannot be used in continuous packing or bottling systems. A non‐destructive method of quality evaluation, using near infrared (NIR) techniques, was tested, by using a portable NIR measuring unit. Spectra of tomato juice of known acid and brix values were determined and, in the wavelength range 703–1124 nm (NIR), a calibration model for acid–brix ratio (ABR) was developed, by using unscrambler software. When used to predict ABR of tomato juice statistical analysis showed minimal standard error (0.009) and satisfactorily high correlation coefficients (0.92) over the wavelength range 1059.5–1124.8 nm, for both calibration and prediction. These values were hardly different from analytical results and the NIR model has potential for non‐destructive prediction of ABR of tomato juice.     

来自植物的天然甜味抑制剂

对国内外天然甜味抑制剂的研究进展进行了综述 ,重点对含有天然甜味抑制成分的 3种植物———匙羹藤、大枣和枳橘的甜味抑制成分及其作用进行了阐述 ,为进一步研究和开发利用天然甜味抑制剂提供参考。     

Dual-attribute Time-intensity Measurement of Sweetness and Peppermint Perception of Chewing Gum

The relationship between duration and maximum intensity of sweetness and peppermint flavor of chewing gum was explored using dual-attribute time-intensity sensory evaluation. Four chewing gum samples, varying in rate of release of sweetness and peppermint flavor were evaluated by 10 trained time-intensity panelists. Chewing gum with a fast release of sweetness and peppermint flavor provided the highest maximum intensity and longest duration of sweetness and peppermint perception. The rate of release of sweetness was more important than rate of release of peppermint flavor in affecting duration of attributes.     

影响浓香型酒甜味因素的探讨

绵甜是浓香型大曲酒的主要特点。影响浓香型大曲酒甜味的因素有：（1）多元醇类、a-联酮类及醛类物质的量比;（2）发酵速度：曲和入窖温度;配料加入池酸度;（3）发酵周期;（4）原料、菌种及菌种数;（5）接酒操作;（6）白酒的贮存处理;（7）勾调处理等。     

Sweetness concentration-response behavior of rebiana at room and refrigerator temperatures

Rebiana is a zero-calorie, natural, high-potency sweetener derived from Stevia rebaudiana Bertoni and comprising almost pure rebaudioside A. Reliable information on its sweetness concentration-response (C-R) behavior is fundamental to rebiana's use as an ingredient. The response curve of rebiana in room-temperature (21 °C) and refrigerated (5 °C) water was determined using 2-alternative forced choice discrimination tests with a minimum of 70 tasters. From a series of panels the proportion of tasters finding different sucrose concentrations sweeter than a fixed concentration of rebiana was plotted against sucrose concentration. The resultant sigmoid curves were linearized by transforming the ordinate axis to a probability scale. This aided experimental design and determination of isosweet concentrations. The latter were deemed to be the sucrose concentration at which 50% of tasters found it to be the sweeter of the pair. Isosweet concentrations of sucrose for seven rebiana concentrations up to 600 mg/L were used to construct a C-R curve for each temperature. Equations were derived for the resultant hyperbolic curves. Rebiana is significantly more potent in cold water. PRACTICAL APPLICATION: Rebiana is a new, zero-calorie, natural, high-potency sweetener derived from the Stevia plant. We have measured the sweetness of rebiana over a range of concentrations at room and refrigerator temperatures. This information will help developers of low-calorie products get the right sweetness level when replacing sugar with rebiana.     

pH和温度对8种甜味剂的甜味释放特征的影响

为探究pH和温度对8种不同甜味剂（蔗糖、果葡糖浆、麦芽糖醇、山梨糖醇、低聚果糖、甜菊糖苷00、甜菊糖苷07和甜菊糖苷14）甜味动态释放特征的影响规律,先通过成对比较法、量值估计法和单因素方差分析,确定了在常温中性条件下,与5 g/dL蔗糖甜度对等的其他7种甜味剂质量浓度。进一步通过时间-强度法（time-intensity）描绘了8种甜味剂在常温中性（25 ℃、pH 7.0）、常温酸性（25 ℃、pH 4.5）和低温中性（4 ℃、pH 7.0）3种条件下的甜味动态释放特征。结果表明,对于大部分样品而言,酸性和低温条件均会降低最大甜味强度,其中,酸性条件对果葡糖浆和甜菊糖苷类样品的降低效果高于低温条件,而对于糖醇类、蔗糖和低聚果糖等样品,低温条件降低效果更显著。此外,各样品的整体甜味持续时间也受到酸性和低温条件的抑制而缩短,且低温条件影响更显著。因此,酸性或低温条件都会抑制不同甜味剂的甜味释放强度或释放时间,但影响程度不同;相比而言,3种条件下,在甜味动态释放特征及变化趋势上,与蔗糖的表现最为接近的是山梨糖醇,其次是果葡糖浆和低聚果糖。     

黄金茶工夫红茶的甜味量化及其与主要滋味物质相关性分析

以黄金茶工夫红茶为研究对象,量化评价茶汤甜味强度,检测主要滋味物质含量,并分析两者相关关系.结果 表明:不同厂家的黄金茶工夫红茶甜味强度差异明显;糖类甜味物质中麦芽糖含量最高,氨基酸类甜味物质中丝氨酸含量最高;甜味物质(包括单糖、双糖和甜味氨基酸)和茶氨酸含量均与甜味强度呈正相关,且糖总量与甜味强度呈显著(P＜0.05...     

甘薯甜度与薯块蒸煮前后糖分的相关性研究

测定了357个干率范围在17.26%～42.42%的甘薯育种选种圃群体蒸煮前后的还原糖、可溶性糖及其甜度。研究表明:甜度与熟薯的可溶性糖、还原糖、生薯可溶性糖呈极显著相关,相关系数分别为0.360**、0.277**0、.274**,与生薯还原糖没有明显相关性,其相关系数仅为0.039。对熟薯的可溶性糖进行分解研究表明,蒸煮过程中产生的还原糖和可溶性多糖对甜度的贡献率分别为47.66%、32.07%。按甜度分级的群体平均数分析,甜度同样与熟薯的可溶性糖、还原糖、生薯可溶性糖呈显著相关性,相关系数分别为0.977**、0.974**0、.962**,与生薯还原糖没有明显相关性,其相关系数仅为0.225。对上述糖分指标的群体分布研究表明,生薯还原糖、生薯可溶性糖、熟薯还原糖呈较窄的正态分布,而熟薯可溶性糖呈较宽的正态分布。综合分析得出,熟薯可溶性糖与甜度具有较高的相关性和品种间的差异,更适合作为甘薯甜度评价的指标和食用品种品质育种指标,甘薯的甜度主要来源于蒸煮过程中产生的糖分而非鲜薯糖分。     

影响凝胶甜味的关键质构因素分析

为了确定影响凝胶甜味的关键质构因素,建立了具有不同质构特征的9种凝胶,采用描述性分析评价其甜味及质构特征,并通过扫描实际咀嚼过程中形成的凝胶碎片进行验证。结果表明,影响凝胶中甜味释放的关键质构因素是易碎性和凝聚性。凝胶碎片扫描结果显示,易碎性较强、凝聚性较弱的样品会形成更多的凝胶碎片和更大的凝胶总表面积,这可能是导致样品甜味更强的原因。此外,较低易碎性样品的甜味还受到润湿性的调控,而高易碎性样品则不受影响。高硬度和低弹性的样品会形成棱角更清晰的凝胶碎片,导致在吞咽前需要经过更多次数的咀嚼,生成更多的凝胶碎片,间接增强凝胶的甜味。     

基于大豆原料蛋白质和氨基酸组成的豆浆甜度预测模型研究

本研究采用电子舌分析了30个大豆品种加工成豆浆的甜度值,运用相关性分析法探究了豆浆甜度值与大豆原料蛋白、氨基酸组成之间的关系,使用逐步回归的方法建立了豆浆甜度的预测模型。结果表明:不同品种的大豆在蛋白质、氨基酸组成上有很大差异。大豆球蛋白(11S)含量(r=0.370)、大豆球蛋白/β-伴大豆球蛋白比率(11S/7S比率)(r=0.436)、丝氨酸(r=0.418)和苏氨酸(r=0.373)含量与豆浆甜度呈显著正相关(p<0.05),α亚基含量(r=-0.460)、β-伴大豆球蛋白(7S)含量(r=-0.428)、蛋氨酸(r=-0.372)和酪氨酸(r=-0.464)含量与豆浆甜度呈显著负相关(p<0.05)。通过逐步回归建立豆浆甜度预测模型的决定系数R²=0.747,方程为:F(甜度预测值)=-0.125×α亚基+3.172×苏氨酸+1.655×丝氨酸-2.894×蛋氨酸-2.097×酪氨酸+9.908,模型验证结果显示,实测值与模型预测值的平均相对误差为4.61%。因此,用本研究模型能准确地预测豆浆甜度。